The present invention relates to a method and circuit for calculating sensor modelling coefficients such as for a pressure or temperature sensor.
In the field of sensor systems, for example pressure and/or temperature sensor systems, it is known for an output of a sensor device to be modelled using one or more equations, and for the output of such a sensor device to be dependent upon higher order input terms. For example, the output of a piezo resistive transducer is dependent upon pressure, as well as being dependent upon temperature terms that could be of higher order. Accordingly, in order to accurately model the characteristics of such sensors, it is necessary to calculate coefficients for the higher order terms.
A traditional approach to calculating such coefficients is to take multiple data readings, use the multiple data readings to establish multiple equations comprising just the unknown coefficients to be calculated, and to solve the equations to determine the coefficient values. A problem with this approach, at least in relation to sensor devices such as piezo resistive transducers is that typically the equation for modelling the characteristics of the sensor device may be of third order or higher. Accordingly, at least four temperature readings are required to solve for the coefficients. Furthermore, the output of such piezo resistive transducers is further dependent upon pressure, thereby requiring additional readings to be taken for different pressure settings. However, taking multiple data readings for different pressure settings in this manner for individual sensor systems is cost prohibitive. Furthermore, it can be cost prohibitive and technically challenging to modify sensors to have a lower order of variation with respect to pressure and/or temperature.
A known solution to this problem is to drop higher order terms from the equations, thereby removing the higher order coefficients and reducing the number of data readings required to calculate remaining coefficients. However, a problem with this solution is that the dropping of higher order terms from the equations can lead to inaccurate estimation of the curve for the sensor device, should the dropped terms have significant weight in terms of performance, and thus can lead to inaccurate modelling of the sensor device.
An alternative known solution to this problem is to use mean values for higher order coefficients, thereby reducing the number of data readings required to be taken. However, the characteristics of individual sensor devices can vary significantly from one fabrication lot to another. Accordingly, a problem with this solution is that the use of mean values for higher order coefficients may also lead to inaccurate estimation of the curve for sensor devices with characteristics that vary from those used to establish the mean values, and thus can also lead to inaccurate modelling of the sensor device. As such, in order for such mean values to be used to reliably and accurately model the characteristics of such sensors, tight design and fabrication tolerances for the sensor devices are required. However, such tight design and fabrication tolerances result in an increase in the costs of production and testing of the sensor devices.